Abstract: The Search Extraction Matching, Draw Attention-Fit Modality, Application Morphing, and Informed Apply Apparatuses, Methods and Systems (“SEMATFM-AMIA”) transforms inputs including new job listing introduction inputs, via SEMATFM-AMIA components (e.g., the conductor component, the resume view controller component, the XY paths handler component, the title handler component, the resume librarian component, and the job listing librarian component), into outputs including relevant resume outputs and/or augmented new job listing record outputs. It is noted that the terms “component” and “object” may be used interchangeably hereinthroughout. In one embodiment, the SEMATFM-AMIA includes an apparatus, comprising: a memory, a component collection in the memory, and a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory.

Abstract: Iterative search of a candidate resume database is performed using computer-implemented methods and accompanying systems, and includes the steps of generating a ranked list of search terms associated with a job candidate search, constructing a search query of the candidate resume database based on the ranked list of search terms, executing the search query on the candidate resume database in a count mode to generate a number of results, evaluating the number of results generated from the execution of the search query by comparing the number of results to individual thresholds within a set of thresholds. Upon determining that the number of results exceeds one or more thresholds, the methods further include retrieving the results from the candidate resume database. Upon determining that the number of results does not exceed one or more thresholds, the methods further include removing a restrictive term from the search query.

Abstract: Iterative search of a candidate resume database is performed using computer-implemented methods and accompanying systems, and includes the steps of generating a ranked list of search terms associated with a job candidate search, constructing a search query of the candidate resume database based on the ranked list of search terms, executing the search query on the candidate resume database in a count mode to generate a number of results, evaluating the number of results generated from the execution of the search query by comparing the number of results to individual thresholds within a set of thresholds. Upon determining that the number of results exceeds one or more thresholds, the methods further include retrieving the results from the candidate resume database. Upon determining that the number of results does not exceed one or more thresholds, the methods further include removing a restrictive term from the search query.

Abstract: The Search Extraction Matching, Draw Attention-Fit Modality, Application Morphing, and Informed Apply Apparatuses, Methods and Systems (“SEMATFM-AMIA”) transforms inputs including new job listing introduction inputs, via SEMATFM-AMIA components (e.g., the conductor component, the resume view controller component, the XY paths handler component, the title handler component, the resume librarian component, and the job listing librarian component), into outputs including relevant resume outputs and/or augmented new job listing record outputs. It is noted that the terms “component” and “object” may be used interchangeably hereinthroughout. In one embodiment, the SEMATFM-AMIA includes an apparatus, comprising: a memory, a component collection in the memory, and a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory.

Abstract: The Search Extraction Matching, Draw Attention-Fit Modality, Application Morphing, and Informed Apply Apparatuses, Methods and Systems (“SEMATFM-AMIA”) transforms inputs including new job listing introduction inputs, via SEMATFM-AMIA components (e.g., the conductor component, the resume view controller component, the XY paths handler component, the title handler component, the resume librarian component, and the job listing librarian component), into outputs including relevant resume outputs and/or augmented new job listing record outputs. It is noted that the terms “component” and “object” may be used interchangeably hereinthroughout. In one embodiment, the SEMATFM-AMIA includes an apparatus, comprising: a memory, a component collection in the memory, and a processor disposed in communication with the memory, and configured to issue a plurality of processing instructions from the component collection stored in the memory.

Abstract: The Social Relation Management Apparatuses, Methods and Systems (“SRM”) transform automated social information gathering inputs via SRM components into activatable social account outputs. A social client outreach apparatus, comprising a processor and memory to obtain inactive client account information from social interaction of other users and then populate an actionable inactive social account with the obtained inactive client account information. Thereafter, the SRM may generate an actionable active social account from the populated account upon receiving an indication and verification of intended use from an interested client.

Abstract: An electronic interview auction method for auctioning an interview for a job, wherein the auction is conducted using at least an auctioneer's computer and one or more bidders' computers communicating electronically over a network, wherein a client may be the auctioneer, or the client and auctioneer may be separate. The method contemplates establishing criteria for the auction and storing the criteria on the auctioneer's computer, allowing potential bidders to access the stored criteria from a bidder's computer by electronic communication with the auctioneer's computer, storing in the auctioneer's computer submitted bid information, including relevant job-related information and a monetary bid, automatically selecting one or more winning bids based on the stored monetary bids, and allowing the user to select other bids with monetary values less than the monetary value of the highest bid.

Abstract: An electronic interview auction method for auctioning an interview for a job, wherein the auction is conducted using at least an auctioneer's computer and one or more bidders' computers communicating electronically over a network, wherein a client may be the auctioneer, or the client and auctioneer may be separate. The method contemplates establishing criteria for the auction and storing the criteria on the auctioneer's computer, allowing potential bidders to access the stored criteria from a bidder's computer by electronic communication with the auctioneer's computer, storing in the auctioneer's computer submitted bid information, including relevant job-related information and a monetary bid, automatically selecting one or more winning bids based on the stored monetary bids, and allowing the user to select other bids with monetary values less than the monetary value of the highest bid.